def LoadModel(model_name="predict_Model"):
model = None
rf = ReadCsvFile()
model = rf.ReadValueFromFile(model_name)
predict_result = None
if model:
# predict_result = model.predict_proba(test_data)
print "Load Model success!"
else:
train_data = rf.ReadTrainFile()
preProce = PreProcess()
train_X,train_lab,train_loc_dic = preProce.preProcessTrainData(train_data)
train_Xc =preProce.getFeatureScaler(train_data)
model = TrainModel(train_Xc,train_lab)
# predict_result = model.predict_proba(test_data)
return model
def LoadModel(model_name="predict_Model_new"):
model = None
rf = ReadCsvFile()
try:
model = rf.ReadValueFromFile(model_name)
print "Load Model success!"
except:
train_data = rf.ReadTrainFile()
print len(train_data)
preP = PreProcess()
train_X,train_lab,loc_dic = preP.preProcessTrainData(train_data)
train_Xc = preP.getFeatureScaler(train_X)
print "Train model"
model = TrainModel(train_Xc,train_lab)
logging.info("save model")
wr = WriteResult()
wr.WriteValueToFile(model,model_name)
return model
def LoadModel(model_name="predict_Model_new"):
model = None
rf = ReadCsvFile()
try:
model = rf.ReadValueFromFile(model_name)
print "Load Model success!"
except:
train_data = rf.ReadTrainFile()
print len(train_data)
preP = PreProcess()
train_X, train_lab, loc_dic = preP.preProcessTrainData(train_data)
train_Xc = preP.getFeatureScaler(train_X)
print "Train model"
model = TrainModel(train_Xc, train_lab)
logging.info("save model")
wr = WriteResult()
wr.WriteValueToFile(model, model_name)
return model
def main():
print "Start......"
rf = ReadCsvFile()
train_data = rf.ReadTrainFile()
preP = PreProcess()
train_X,train_lab,loc_dic = preP.preProcessTrainData(train_data)
train_Xc = preP.getFeatureScaler(train_X)
# print "Train model"
# TrainModel(train_Xc,train_lab)
# train_lab = None
# loc_dic = None
# train_data = None
# train_X = None
# train_Xc = None
# with open(Config.ResultDataPath+"result.csv","w") as fp:
# print "清空文件","result.csv"
model = LoadModel()
print model
print "精确率：{0}".format(model.score(train_Xc[2000:3000],train_lab[2000:3000]))
def main():
print "Start......"
rf = ReadCsvFile()
train_data = rf.ReadTrainFile()
preP = PreProcess()
train_X, train_lab, loc_dic = preP.preProcessTrainData(train_data)
train_Xc = preP.getFeatureScaler(train_X)
# print "Train model"
# TrainModel(train_Xc,train_lab)
# train_lab = None
# loc_dic = None
# train_data = None
# train_X = None
# train_Xc = None
# with open(Config.ResultDataPath+"result.csv","w") as fp:
# print "清空文件","result.csv"
model = LoadModel()
print model
print "精确率：{0}".format(
model.score(train_Xc[2000:3000], train_lab[2000:3000]))